Exploring the Variations and Influencing Factors of Land Surface Temperature in the Urban Agglomeration on the Northern Slope of the Tianshan Mountains

Hongwu Liang, Alimujiang Kasimu (), Haitao Ma, Yongyu Zhao, Xueling Zhang and Bohao Wei
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Hongwu Liang: School of Geography and Tourism, Xinjiang Normal University, Urumqi 830054, China
Alimujiang Kasimu: School of Geography and Tourism, Xinjiang Normal University, Urumqi 830054, China
Haitao Ma: Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Yongyu Zhao: School of Geography and Tourism, Xinjiang Normal University, Urumqi 830054, China
Xueling Zhang: School of Geography and Tourism, Xinjiang Normal University, Urumqi 830054, China
Bohao Wei: School of Geography and Tourism, Xinjiang Normal University, Urumqi 830054, China

Sustainability, 2022, vol. 14, issue 17, 1-22

Abstract: Changes in land surface temperature (LST) can have serious impacts on the water cycle and ecological environment evolution, which in turn threaten the sustainability of ecosystems. The urban agglomeration on the northern slopes of the Tianshan Mountains (UANSTM) is located in the arid and semi-arid regions of northwest China, with an extremely fragile ecological environment and sensitive to climate change. However, studies on the LST of the UANSTM have not received much attention. Therefore, this study explored the spatial distribution pattern, fluctuation characteristics, and influencing factors of the LST of the UANSTM from 2005 to 2021 based on MODIS time series LST data and the geo-detector model with optimal parameters. The results show that the UANSTM is dominated by medium- and high-temperature classes, with high- and extremely high-temperature classes clustered in Turpan City. The daytime and nighttime LST patterns are significantly different, with a typical “daytime cold island and nighttime heat island” feature in the oasis region. During 2005–2021, LST fluctuated greatly in the northwestern part of the UANSTM, with LST showing an increasing trend during both daytime and nighttime, and the warming rate was more intense during daytime than nighttime. The increasing trend of LST in Urumqi, Changji Hui Autonomous Prefecture, Shihezi, and Wujiaqu is very significant and will remain consistent in the future. Precipitation, DEM, and AOD are the most important influencing factors of LST in the UANSTM, where precipitation and DEM are negatively correlated with LST, and AOD is positively correlated with LST. Land cover factors (LULC, NDVI,, and NDBSI) are the next most influential, and socioeconomic factors (NTL, GDP, and POP) are the least influential. The results of this study can provide a scientific reference for the conservation and sustainable development of the ecological environment of the UANSTM.

Keywords: land surface temperature; urban agglomeration on the northern slope of the Tianshan Mountains; influencing factors; geo-detector model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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